• Corpus ID: 27767601

Querying Freesound with a microphone

@inproceedings{Roma2015QueryingFW,
  title={Querying Freesound with a microphone},
  author={Gerard Roma and Xavier Serra},
  year={2015}
}
On the web, searching for sounds is usually limited to text queries. This requires adding textual descriptions to each audio file, which is indexed effectively as a text document. Recent developments in browser technologies allow developers to access the audio input or microphone of the computer, enabling Query by Example (QbE) applications. We present a demonstration system that allows users to make queries on Freesound.org by recording audio in the browser. A basic prototype is available… 
mtg.upf.edu
22 Citations
Highly Influential Citations
3
Background Citations
14
Methods Citations
3

Figures from this paper

22 Citations

Citation Type

Citation Type

Vroom!: A Search Engine for Sounds by Vocal Imitation Queries
TLDR
Results showed that Vroom! received significantly higher search satisfaction ratings than TextSearch did for sound categories that were difficult for subjects to describe by text, and suggested that QBV, as a complimentary search approach to existing text-based search, can improve both search results and user experience.
Sound Sharing and Retrieval
TLDR
This chapter describes how to build an audio database by outlining different aspects to be taken into account and discusses metadata-based descriptions of audio content and different searching and browsing techniques that can be used to navigate the database.
An Archival Echo: Recalling the public domain through real-time query by vocalisation
TLDR
A novel system that uses real-time query by vocalization to retrieve sounds extracted from chart hit singles of the 1960s and enables the user, or performer, to generate a cascade of archival echoes from vocalisations.
Supervised and Unsupervised Sound Retrieval by Vocal Imitation
TLDR
Experiments show that sound retrieving performance by automatically learned features outperform those carefully handcrafted ones that were used in existing systems in both supervised and unsupervised settings.
Vocal imitation for query by vocalisation
TLDR
The ability of musicians to vocalise synthesised and percussive sounds is investigated, and the suitability of different audio features for predicting the perceptual similarity between vocal imitations and imitated sounds is evaluated.
IMISOUND: An Unsupervised System for Sound Query by Vocal Imitation
  • Yichi Zhang, Zhiyao Duan
  • Computer Science
    2016 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)
  • 2017
TLDR
A novel human-computer interaction system called IMISOUND that listens to a vocal imitation and retrieves similar sounds from a sound library and significantly outperforms an unsupervised MFCC-based baseline system, validating the advantage of the SAE feature representation.
Sound Search by Text Description or Vocal Imitation?
TLDR
A subjective study to compare two web-based search engines for sound, one by vocal imitation (Vroom!) and the other by text description (TextSearch), which showed that Vroom! received significantly higher search satisfaction ratings than TextSearch did for sound categories that were difficult for subjects to describe by text.
DESCRIPTION OR VOCAL IMITATION ?
TLDR
A subjective study to compare two web-based search engines for sound, one by vocal imitation (Vroom!) and the other by text description (TextSearch), which showed that Vroom! received significantly higher search satisfaction ratings than TextSearch did for sound categories that were difficult for subjects to describe by text.
Non-speech voice for sonic interaction: a catalogue
TLDR
It is pointed out that while voice-based techniques are already being used proficiently in sound retrieval and sound synthesis, their use in sound design is still at an exploratory phase.
Siamese Style Convolutional Neural Networks for Sound Search by Vocal Imitation
TLDR
Experimental results show that both versions of the proposed Siamese style convolutional neural networks outperform a state-of-the-art system for sound search by vocal imitation, and the performance can be further improved when they are fused with the state of the art system.
...
1
2
3
...

References

SHOWING 1-7 OF 7 REFERENCES
Sound Retrieval From Voice Imitation Queries In Collaborative Databases
TLDR
This work introduces the use of non-speech voice imitations as input queries in a large user-contributed sound repository and addresses first the analysis of the human voice properties when imitating sounds, and studies the automatic classification of voice Imitations in clusters by means of user experiments.
Fast query by example of environmental sounds via robust and efficient cluster-based indexing
TLDR
This work explores several cluster-based indexing approaches, namely non-negative matrix factorization (NMF) and spectral clustering to efficiently organize and quickly retrieve archived audio using the QBE paradigm, and initial results indicate significant improvements over both exhaustive search schemes and traditional K- means clustering, and excellent overall performance in the example-based retrieval of environmental sounds.
Freesound 2: An Improved Platform for Sharing Audio Clips
Freesound.org is an online collaborative sound database where people from different disciplines share recorded sound clips under Creative Commons licenses. It was started in 2005 and it is being…
Classification of sound clips by two schemes: Using onomatopoeia and semantic labels
Using the recently proposed framework for latent perceptual indexing of audio clips, we present classification of whole clips categorized by two schemes: high-level semantic labels and the mid-level…
Vocal Imitations and the Identification of Sound Events
It is commonly observed that a speaker vocally imitates a sound that she or he intends to communicate to an interlocutor. We report on an experiment that examined the assumption that vocal imitations…
ESSENTIA: an open source library for audio analysis
Data-Driven Concatenative Sound Synthesis
  • PhD thesis,
  • 2004